TY - JOUR
T1 - Privacy-preserving image retrieval for medical IoT systems
T2 - A blockchain-based approach
AU - Shen, Meng
AU - Deng, Yawen
AU - Zhu, Liehuang
AU - Du, Xiaojiang
AU - Guizani, Nadra
N1 - Publisher Copyright:
© 1986-2012 IEEE.
PY - 2019/9/1
Y1 - 2019/9/1
N2 - With the advent of medical IoT devices, the types and volumes of medical images have significantly increased. Retrieving of medical images is of great importance to facilitate disease diagnosis and improve treatment efficiency. However, it may raise privacy concerns from individuals, since medical images contain patients' sensitive and private information. Existing studies on retrieval of medical data either fail to protect sensitive information of medical images or are limited to a single image data provider. In this article, we propose a blockchain-based system for medical image retrieval with privacy protection. We first describe the typical scenarios of medical image retrieval and summarize the corresponding requirements in system design. Using the emerging blockchain techniques, we present the layered architecture and threat model of the proposed system. In order to accommodate large-size images with storage-constrained blocks, we capture a carefully selected feature vector from each medical image and design a customized transaction structure, which protects the privacy of medical images and image features. We also discuss the challenges and opportunities of future research.
AB - With the advent of medical IoT devices, the types and volumes of medical images have significantly increased. Retrieving of medical images is of great importance to facilitate disease diagnosis and improve treatment efficiency. However, it may raise privacy concerns from individuals, since medical images contain patients' sensitive and private information. Existing studies on retrieval of medical data either fail to protect sensitive information of medical images or are limited to a single image data provider. In this article, we propose a blockchain-based system for medical image retrieval with privacy protection. We first describe the typical scenarios of medical image retrieval and summarize the corresponding requirements in system design. Using the emerging blockchain techniques, we present the layered architecture and threat model of the proposed system. In order to accommodate large-size images with storage-constrained blocks, we capture a carefully selected feature vector from each medical image and design a customized transaction structure, which protects the privacy of medical images and image features. We also discuss the challenges and opportunities of future research.
UR - http://www.scopus.com/inward/record.url?scp=85073332226&partnerID=8YFLogxK
U2 - 10.1109/MNET.001.1800503
DO - 10.1109/MNET.001.1800503
M3 - Article
AN - SCOPUS:85073332226
SN - 0890-8044
VL - 33
SP - 27
EP - 33
JO - IEEE Network
JF - IEEE Network
IS - 5
M1 - 8863723
ER -